class_docstr: Abstract base class for test cases.
  
  Intentionally not a sub-class of unittest.TestCase so that unittest / pytest
  don't run it directly. unitest.TestCase is mixed in as another base class when
  creating concrete sub-types. See MakeTestCase().
class_docstr_tok: ["Abstract","base","class","for","test","cases",".","Intentionally","not","a","sub-class","of","unittest.TestCase","so","that","unittest","\/","pytest","do","n't","run","it","directly",".","unitest.TestCase","is","mixed","in","as","another","base","class","when","creating","concrete","sub-types",".","See","MakeTestCase","(",")","."]
code: def test_native_dropout(self):
      graph_ir = """
          graph(%1 : Float(2, 3)):
            %2 : float = prim::Constant[value=0.0]()
            %training : bool = prim::Constant[value=1]()
            %3 : Tensor, %4 : Tensor = aten::native_dropout(%1, %2, %training)
            return (%3, %4)
          """
      a = torch.randn(2, 3)
      self.run_test(graph_ir, (a,))
  
file_path: pytorch/test/onnx/test_pytorch_jit_onnx.py
imports: import onnxruntime
  import pytorch_test_common
  import torch
  from pytorch_test_common import skipIfNoCuda
  from torch.onnx import verification
  from torch.onnx._globals import GLOBALS
  from torch.testing._internal import common_utils
label_desc: Use image node_id 8 for calling the _TestJITIRToONNX obj's underlying member method code with example usage: obj.test_native_dropout() without return types